Acute respiratory infections (ARIs) represent a major cause of morbidity and mortality in the world1. About 20% of all deaths in children younger than 5 years of age are due to ARIs, with among those 90% attributed to pneumonia. This translates into approximately 150 million cases of pneumonia, with between 11-20 million children hospitalized, and more than 2 million dying from the disease (WHO). Even in the US, influenza and pneumonia are the eighth leading cause of death, the majority of which are infants and the elderly (American Lung Association). The ability to identify etiological agents of respiratory infections remains inadequate. Indeed, there are major obstacles: 1) bacteria and viruses are not always present in samples; 2) determination of infectious agent can take days; and 3) multiple tests are often required to determine source. Moreover, current tests for diagnosis are poor at assessing disease severity and, to date, only a few studies have examined the usefulness of biomarker panels that might prove beneficial in the differentiation between bacterial and viral respiratory tract infections2. Such diagnostic obstacles can delay initiation o appropriate therapy, resulting in unnecessary morbidity, death, and healthcare costs3. Rapid advances in genomics research can be leveraged to dramatically improve the management of ARIs. Recently, we developed modular analysis approaches to evaluate whole genome blood microarray profiles from 410 samples comprised of patients clinically diagnosed with ARIs and healthy controls. The meta-analysis identified 10 gene sets (or modules) that were able to discriminate between bacterial and viral agents responsible for ARIs with high accuracy. Our goal is to develop AResT (Acute Respiratory-related Transcripts), an innovative multivariate RNA assay designed for rapid triage of patients with ARIs. The first step in the development process is to reduce the current number of transcript targets within these 10 modules (n=694) while enabling the use of a PCR-based detection method, and improve the scoring algorithm against an independent set of blood samples from patients diagnosed with well-characterized ARIs. The specific aims are to: 1) validate a PCR-based multivariate RNA profiling assay using banked patient samples; 2) improve the scoring algorithm while determining the minimum probe set; and 3) compare AResT test accuracy against commonly used blood biomarkers PCT and CRP.